Jiang C, Wang G, Liu J, et al. 3DSFLabelling: Boosting 3D Scene Flow Estimation by Pseudo Auto-labelling[J]. arXiv preprint arXiv:2402.18146, 2024. 写在最后
if the estimated pixel depths match those provided by LiDAR, pseudo-LiDAR with any LiDAR-based detector should be able to achieve the same performance depth estimation from stereo pairs of images (Mayer et al., 2016; Yamaguchi et al., 2014; Chang & Chen, 2018) are more accurate than that...
(ICLR) Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving - mileyan/Pseudo_Lidar_V2
首先利用DRON或PSMNET从单目 (Monocular)或双目 (Stereo)图像获取对应的深度图像(depth map);然后将原图像结合深度信息得到伪雷达点云 (pseudo-LiDAR);最后用pseudo-LiDAR代替原始雷达点云,以3D point cloud和鸟瞰图(bird's eye view)的形式,分别在LiDAR-based的F-PointNet以及AVOD上与图像的正视图(front view)表示...
课件成果介绍pseudo lidar from visual depth estimation bridging the gap 3d object detection for autonomous driving.pdf,Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving Yan Wang, Wei-Lun Chao, Divyan
C Poullis,S You - International Conference on 3d Imaging 被引量: 24发表: 2011年 SeFlow: A Self-Supervised Scene Flow Method in Autonomous Driving Scene flow estimation predicts the 3D motion at each point in successive LiDAR scans. This detailed, point-level, information can help autonomous ve...
This paper has been accpeted by Conference on Computer Vision and Pattern Recognition (CVPR) 2019. Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving byYan Wang,Wei-Lun Chao,Divyansh Garg,Bharath Hariharan,Mark CampbellandKilian Q. Weinberger...
Synchronizing 3D point cloud from 3D scene flow estimation with 3D Lidar and RGB cameradoi:info:doi/10.2352/ISSN.2470-1173.2018.18.3DIPM-426Usami, HirokiSaito, HideoKawai, JunItani, NorikoElectronic Imaging
Deformation and Correspondence Aware Unsupervised Synthetic-to-Real Scene Flow Estimation for Point Clouds [scene flow; Github] LiDAR Snowfall Simulation for Robust 3D Object Detection [det; Github] Text2Pos: Text-to-Point-Cloud Cross-Modal Localization [localization; PyTorch] Stratified Transformer for...
Figure 4. Flow chart of 3D laser data acquisition. After the field survey of the underground mine, the control points were arranged along the roadway by means of Total Station Branch traverse, and the 3D coordinates of six target points were collected (the coordinate system is CGCS2000 coordin...